Current Vision Research Articles

An attention fused sequence -to-sequence convolutional neural network for accurate solar irradiance forecasting and prediction using sky images

The challenge of accurately forecasting ultra-short-term solar irradiance for photovoltaic systems is complicated by rapidly changing weather, and while ground-based sky images offer potential improvements, effectively extracting spatiotemporal data from these images remains a significant hurdle for current computer vision models. A new hybrid model, "An Attention Fused Sequence-to-Sequence Convolutional Neural Network," is being developed to address this challenge. The model predicts intra-hour GHI, DNI, and DHI with a 10-min lead time by combining a Convolutional Neural Network (for spatial feature extraction from sky images), an attention mechanism (to focus on relevant regions), and a sequence-to-sequence model (for temporal feature extraction from time-series data). The proposed Model is trained using the NREL Solar Radiation Research Laboratory Dataset while evaluating the model with the Mean Bias Error, Mean Absolute Error, Root Mean Squared Error, R Squared, and forecasting skill score. The 10-min and sequence length 2 interval is considered to be the best performing across most of the evaluation metrics with an MBE value is 2.321 W/m2, MAE value of 39.490 W/m2, RMSE value of 62.086 W/m2, R2 value is 0.909 W/m2, FSS value of 23.589 W/m2 and an MBE of 4.876 W/m2, MAE of 56.887 W/m2, RMSE of 85.346 W/m2, R2 of 0.834 and FSS of 24.881 W/m2 respectively. Furthermore, the sensitivity analysis reveals that the proposed model's performance is influenced by both the sequence length and the lead time. The proposed framework outperforms other techniques for ultra-short-term PV generation forecasting, demonstrating its potential for practical deployment in PV systems to improve grid reliability and energy management.

Manipulator with Integrated Flexible Tactile Sensing Arrays for Kiwifruit Ripeness and Size Classification.

Fruit grading for ripeness and size is an essential process in the supply chain. Incorrect grading can easily lead to spoiled and degraded fruits entering the market, reducing consumers' confidence in purchasing. At the same time, it is easy to cause the fruit supply chain to reduce profits, unreasonable resource allocation, and related practitioners' income. The current mainstream machine vision grading and manual grading in the production line have dilemmas such as susceptibility to environmental interference, inconsistent grading standards, high cost, and labor shortage. To overcome these problems, this study proposes an integrated flexible tactile sensing array (3 × 4) manipulator for efficient, stable, low-cost, and accurate ripeness and size grading of kiwifruit. The flexible sensing manipulator grasps the kiwifruit, detects the hardness of the kiwifruit by relying on tactile sensing, and determines the ripeness level based on the hardness. The size of the kiwifruit is also differentiated according to whether there is a significant change in the resistance of the topmost sensing unit of the flexible pressure sensor array. The 0, 1, 2, 3, 4, and 5 anomalies that may occur in actual production were tested and combined with machine learning KNN, SVM, and RF algorithms for data modeling and grading. The results show that the lowest accuracy of 0, 1, 2, 3, 4, and 5 possible outliers is 86.67% (KNN), 95.83% (SVM), and 92.5% (RF), respectively. KNN has the lowest classification effect, and SVM has the best. This study overcomes the drawbacks of inefficient destructive detection and unstable manual detection and makes up for the vulnerability of single machine vision to interference from environmental factors. This study can alleviate the challenges caused by fruit wastage and promote the sustainable production and consumption of the fruit industry chain.

Efficient detection method for tiny defects on printed circuit boards based on focus information transfer and structurally flexible head

Abstract Aiming at the conflict between the defect feature recognition capability and the detection speed of current vision inspection techniques in the task of detecting tiny defects in printed circuit boards (PCBs). In this paper, we proposed an EPD-YOLO with a focus information transfer (FIT) structure and a structurally flexible head (SFHead). While improving the network’s ability to recognize tiny defects in similar PCBs through FIT, the feature information capturing capability of the dual SFHead structure is utilized to ensure detection accuracy and improve real-time detection speed. Experimental results show that the proposed EPD-YOLO has a mAP of 97.6 % , while the number of network parameters is only 5.13M, and it takes only 7.4 ms to detect an image, which achieves a better balance between accuracy and speed.

Refractive errors, amblyopia risk factors and vision screening in children aged 7–10 years in Aotearoa New Zealand

ABSTRACT Clinical relevance Vision screening is important for detecting undiagnosed vision conditions that are common in school-aged children. However, current vision screening protocols are poor at detecting vision conditions that are most common in the Aotearoa New Zealand paediatric population. Background Uncorrected refractive error and amblyopia are the most common causes of visual impairment in children. The most appropriate vision screening method depends on the refractive error profile of the population. This study aimed to: estimate the prevalence of refractive errors and amblyopia risk factors among children living in Aotearoa New Zealand; describe previous participation in preschool vision screening and determine the diagnostic accuracy of potential screening methods. Methods Children aged 7–10 years received comprehensive eye examinations, including cycloplegic refraction, in their school. Eye examination results were assessed for refractive error and amblyopia risk factors. The sensitivity and specificity of individual vision tests for detecting any vision conditions was calculated to assess the most effective tests for vision screening. Results Eye examinations were completed for 237 children and cycloplegic refraction data was available for 220 of these children. Significant refractive error (need for glasses) was detected in 23.6% of children (7.7% myopia, 7.7% hyperopia, 15.0% astigmatism). Amblyopia risk factors were detected in 9.1% of children. Preschool vision screening had been completed by 78.5% of children. Distance visual acuity screening alone had a sensitivity of 39% for detecting vision conditions, with addition of the Spot Vision Screener improving sensitivity to 65%. Conclusion Astigmatism is the most frequent refractive error among children aged 7–10 years living in Aotearoa New Zealand. Distance visual acuity screening alone is ineffective in detecting refractive error in children in Aotearoa New Zealand. Further research investigating refractive errors across the paediatric population in Aotearoa New Zealand is required to determine the optimal timing and appropriate protocols for school-aged vision screening.

Transcriptomic analyses in the gametophytes of the apomictic fern Dryopteris affinis

Main conclusionA novel genomic map of the apogamous gametophyte of the fern Dryopteris affinis unlocks oldest hindrance with this complex plant group, to gain insight into evo-devo approaches.The gametophyte of the fern Dryopteris affinis ssp. affinis represents a good model to explore the molecular basis of vegetative and reproductive development, as well as stress responses. Specifically, this fern reproduces asexually by apogamy, a peculiar case of apomixis whereby a sporophyte forms directly from a gametophytic cell without fertilization. Using RNA-sequencing approach, we have previously annotated more than 6000 transcripts. Here, we selected 100 of the inferred proteins homolog to those of Arabidopsis thaliana, which were particularly interesting for a detailed study of their potential functions, protein–protein interactions, and distance trees. As expected, a plethora of proteins associated with gametogenesis and embryogenesis in angiosperms, such as FERONIA (FER) and CHROMATING REMODELING 11 (CHR11) were identified, and more than a dozen candidates potentially involved in apomixis, such as ARGONAUTE family (AGO4, AGO9, and AGO 10), BABY BOOM (BBM), FASCIATED STEM4 (FAS4), FERTILIZATION-INDEPENDENT ENDOSPERM (FIE), and MATERNAL EFFECT EMBRYO ARREST29 (MEE29). In addition, proteins involved in the response to biotic and abiotic stresses were widely represented, as shown by the enrichment of heat-shock proteins. Using the String platform, the interactome revealed that most of the protein–protein interactions were predicted based on experimental, database, and text mining datasets, with MULTICOPY SUPPRESSOR OF IRA4 (MSI4) showing the highest number of interactions: 16. Lastly, some proteins were studied through distance trees by comparing alignments with respect to more distantly or closely related plant groups. This analysis identified DCL4 as the most distant protein to the predicted common ancestor. New genomic information in relation to gametophyte development, including apomictic reproduction, could expand our current vision of evo-devo approaches.

Research and Analysis on Regional Heterogeneity of Educational Development Level and Economic Growth

China's rapid economic development over the past 40 years has improved the overall quality of life of the population but has also brought about uneven distribution of resources. The problem of educational inequality under the conditions of uneven distribution of economic development is one of the main problems that China needs to solve. Solving the problem of educational inequality plays a positive role in social fairness, justice, and long-term stability. Based on the above background, this paper focuses on the development of education policies in recent decades, the gains and losses of education poverty alleviation, the causes of the "involutionary" competition in urban education, and the effectiveness of relevant policies. It is recommended to improve the allocation of educational resources further and invest appropriate resources in the construction of vocational and technical schools to match the current development vision of China's economy. This paper suggests that students from poor areas be allowed to study in economically developed areas to improve educational resources in poor areas in the short term. This paper also calls on the government to establish a long-term mechanism to promote the growth of the education industry and promote a positive cycle of educational development and economic development.

Learning 3D human–object interaction graphs from transferable context knowledge for construction monitoring

We propose a novel framework for detecting 3D human–object interactions (HOI) in construction sites and a toolkit for generating construction-related human–object interaction graphs. Computer vision methods have been adopted for construction site safety surveillance in recent years. The current computer vision methods rely on videos and images, with which safety verification is performed on common-sense knowledge, without considering 3D spatial relationships among the detected instances. We propose a new method to incorporate spatial understanding by directly inferring the interactions from 3D point cloud data. The proposed model is trained on a 3D construction site dataset generated from our crafted simulation toolkit. The model achieves 54.11% mean interaction over union (mIOU) and 72.98% average mean precision(mAP) for the worker–object interaction relationship recognition. The model is also validated on PiGraphs, a benchmarking dataset with 3D human–object interaction types, and compared against other existing 3D interaction detection frameworks. It was observed that it achieves superior performance from the state-of-the-art model, increasing the interaction detection mAP by 17.01%. Besides the 3D interaction model, we also simulate interactions from industrial surveillance footage using MoCap and physical constraints, which will be released to foster future studies in the domain.

The right to a fair trial in the light of the minimum guarantee of legal assistance in the practice of the European Court of Human Rights

The research attempts to form the essence of the modern understanding of the right to a fair trial through the prism of the minimum guarantee of legal assistance. Attention is drawn to the fact that the European Convention itself does not define the mechanism of its application, which in turn complicates its application by different states with certain differences in legal systems. In this regard, it is substantiated that by ruling on the application of the European Convention, the European Court of Human Rights (ECHR) sets the direction for building one of the most effective systems of human rights protection, which is subsequently manifested in the national systems of the Convention member states. In view of this, the article analyses the most important, key and modern practice of the ECHR in relation to consideration of applications for violation of the minimum guarantee of legal assistance in the context of violation of the right to a fair trial and summarises it, as well as identifies the risks of such an approach. In addition, the paper analyses the current conceptual vision of such transformations from the point of view of legal scholars, both academics and practitioners. In the course of analysis of modern ECHR judgments, the author found that in a significant number of them the Court indicates that the mere violation of the minimum guarantee of legal assistance does not automatically mean a violation of the right to a fair trial, and the author emphasizes the possible risks of such an interpretation, in particular, for the States which are leaders in violation of the guarantee of legal assistance, where the specifics of national systems reflect a systematic violation of this right. It is determined that the application of the minimum guarantee of legal assistance is not limited to criminal proceedings, and the court is not the only institution that must comply with this guarantee to ensure fairness of the proceedings. It is also emphasised that the practice of applying this guarantee cannot be limited to court proceedings only. The author also suggests improving the legal technique of implementing the European Convention into national legislation by amending its translation into Ukrainian.

The influence of absolute and relative spatial cues on change detection performance

ABSTRACT Two experiments investigate how absolute and relative spatial cues influence perceptual comparisons between visual short-term memory (VSTM) and current vision. The core question concerned the role of task demands in this process. Two tasks were given across two experiments, differing in the extent they required object-level comparisons. Experiment 1, a feature comparison task, required reporting if any new colour was present in the second of two interleaved displays of four colours inside a surround; Experiment 2, an object comparison task, required report of any changes in colour-shape pairings in the second of two interleaved displays of four coloured shapes in a surround. Absolute and relative spatial organization was manipulated in both experiments by presenting compared displays on the same or contralateral sides, and by having the second display items in the same locations within the surround, in new locations, or repositioned into previous locations of other items. In sensitivity, both tasks showed an advantage for absolute spatial cues, but only the object task showed an advantage for relative spatial cues. In bias, both tasks were similarly influenced by both absolute and relative cues. Results suggest relative spatial cues are always available but only used when making object-level comparisons.

A Deep Learning Approach to Distance Map Generation Applied to Automatic Fiber Diameter Computation from Digital Micrographs.

Precise measurement of fiber diameter in animal and synthetic textiles is crucial for quality assessment and pricing; however, traditional methods often struggle with accuracy, particularly when fibers are densely packed or overlapping. Current computer vision techniques, while useful, have limitations in addressing these challenges. This paper introduces a novel deep-learning-based method to automatically generate distance maps of fiber micrographs, enabling more accurate fiber segmentation and diameter calculation. Our approach utilizes a modified U-Net architecture, trained on both real and simulated micrographs, to regress distance maps. This allows for the effective separation of individual fibers, even in complex scenarios. The model achieves a mean absolute error (MAE) of 0.1094 and a mean square error (MSE) of 0.0711, demonstrating its effectiveness in accurately measuring fiber diameters. This research highlights the potential of deep learning to revolutionize fiber analysis in the textile industry, offering a more precise and automated solution for quality control and pricing.

Rehab-AMD: co-design of an application for visual rehabilitation and monitoring of Age-related Macular Degeneration

BackgroundThe increasing demand for remote medical care, driven by digital healthcare advancements and the COVID-19 pandemic, necessitates effective solutions tailored to patients and healthcare practitioners. Co-design, involving collaboration between software developers, patients, and healthcare practitioners, prioritizes end-user needs. Research indicates that integrating patient perspectives enhances user experience and usability. However, its application in healthcare has been limited to small projects. This work focuses on co-designing a technological solution to enhance the monitoring and visual rehabilitation of individuals with Age-Related Macular Degeneration (AMD), a condition that significantly impacts the quality of life in people over 60. Current vision rehabilitation systems lack personalization, motivation, and effective progress monitoring. Involving patients and healthcare practitioners in the design process aims to ensure the final product meets their needs.MethodsThe project employs iterative and collaborative principles, involving a vision rehabilitation expert and two AMD patients as active users in the application’s development and validation. The process begins by establishing requirements for user accounts and rehabilitation exercises. It continues with an initial approach extended through user validation. Co-design is facilitated by specific workshops marking each project iteration, totaling four workshops, along with continuous communication sessions between experts and developers to validate design decisions. Initial requirements gathering and constant feedback from end-users, the visual rehabilitator, and patients are crucial for refining the product effectively.ResultsThe workshops produced a prototype featuring a test to monitor changes and progression and 15 visual rehabilitation exercises. Numerous patient and vision rehabilitation-driven software modifications led to a final design that is responsive and adaptive to end-user needs.ConclusionsThe Rehab-AMD pilot project aims to develop a collaborative and adaptive software solution for AMD rehabilitation by actively involving stakeholders and applying iterative design principles. Co-design in the Rehab-AMD solution proves to be a methodology that identifies usability issues and needs from the initial design stages. This approach ensures that software developers create a final product that is genuinely useful and manageable for people with AMD and the targeted vision rehabilitators.

Artificial Amacrine Retinal Circuits.

Event-based imaging represents a new paradigm in visual information processing that addresses the speed and energy efficiency shortcomings inherently present in the current complementary metal oxide semiconductor-based machine vision. Realizing such imaging systems has previously been sought using very large-scale integration technologies that have complex circuitries consisting of many photodiodes, differential amplifiers, capacitors, and resistors. Here, we demonstrate that event-driven sensing can be achieved using a simple one-resistor, one-capacitor (1R1C) circuit, where the capacitor is modified with colloidal quantum dots (CQDs) to have a photoresponse. This sensory circuit emulates the motion-tracking function of the biological retina, in which the amacrine cells in the bipolar-to-ganglion synaptic pathway produce a transient spiking signal only in response to changes in light intensity but remain inactive under constant illumination. When extended to a 2D imaging array, the individual sensors work independently and output signals only when a change in the light intensity is detected; hence, the concept of the frame in image processing is thereby removed. In this work, we present the fabrication and characterization of a CQD photocapacitor-based 1R1C circuit that has a spectral response at 1550 nm in the short-wave infrared (SWIR). We report on the key performance parameters including peak responsivity, noise, and optical noise equivalent power and discuss the operating mechanism that is responsible for spiking responses in these artificial retinal circuits. The present work sets the foundation for expanding the bioinspired vision sensor capability toward midwave infrared (MWIR) and long-wave infrared (LWIR) spectral regions that are invisible to human eyes and mainstream semiconductor technologies.

AI-based detection and identification of low-level nuclear waste: a comparative analysis

Ensuring environmental safety and regulatory compliance at Department of Energy (DOE) sites demands an efficient and reliable detection system for low-level nuclear waste (LLW). Unlike existing methods that rely on human effort, this paper explores the integration of computer vision algorithms to automate the identification of such waste across DOE facilities. We evaluate the effectiveness of multiple algorithms in classifying nuclear waste materials and their adaptability to newly emerging LLW. Our research introduces and implements five state-of-the-art computer vision models, each representing a different approach to the problem. Through rigorous experimentation and validation, we evaluate these algorithms based on performance, speed, and adaptability. The results reveal a noteworthy trade-off between detection performance and adaptability. YOLOv7 shows the best performance and requires the highest effort to detect new LLW. Conversely, OWL-ViT has lower performance than YOLOv7 and requires minimal effort to detect new LLW. The inference speed does not strongly correlate with performance or adaptability. These findings offer valuable insights into the strengths and limitations of current computer vision algorithms for LLW detection. Each developed model provides a specialized solution with distinct advantages and disadvantages, empowering DOE stakeholders to select the algorithm that aligns best with their specific needs.

Who Says You can't go FAST at Night? Use of a Novel Ultrasound-Capable Night Vision Device for Prehospital Medical Personnel to Identify Noncompressible Truncal Hemorrhage.

Early detection of abdominal hemorrhage via ultrasound has life-saving implications for military and civilian trauma. However, strict adherence to light discipline may prohibit the use of ultrasound devices in the deployed setting. Additionally, current night vision devices remain noncompatible with ultrasound technology. This study sought to assess an innovative night vision device with ultrasound capable picture-in-picture display via a intraabdominal hemorrhage model to identify noncompressible truncal hemorrhage in blackout conditions. 8 post mortem fetal porcine specimens were used and divided into 2 groups: intrabdominal hemorrhage (n = 4) vs no hemorrhage (n = 4). Intrabdominal hemorrhage was modeled via direct injection of 200mL of normal saline into the peritoneal cavity. Under blackout conditions, 5 participants performed a focused assessment with sonography for trauma (FAST) exam on each model using the prototype ultrasound-capable night vision device. Of the 40 FAST exams performed, 95% (N = 38) resulted in the correct identification of intraabdominal hemorrhage. Of the incorrectly identified exams, both were false positives resulting in a 100% sensitivity, 90% specificity, 91% positive predictive value, and a 100% negative predictive value. All participants noted the novel device was easy to use and provided superior visualization for performing FAST exams under blackout conditions. The ultrasound-enabled night vision prototype demonstrated promising results in identifying noncompressible truncal hemorrhage while maintaining strict light discipline in blackout conditions. Further research efforts should be directed at assessing the ability of providers to perform procedures in blackout conditions using the ultrasound-enabled prototype night vision device.

Eye-Tracking Devices for Virtual and Augmented Reality Metaverse Environments and Their Compatibility with the European Union General Data Protection Regulation

Even though the Metaverse from science fiction is not a reality yet, it is possible to take a glimpse into how it might look like. However, the current vision of the Metaverse does not only encompass software. A great deal of companies is complementing their Metaverse projects with Virtual and Augmented Reality devices such as headsets and glasses. In this line, one of the last technological advancements in virtual and augmented reality devices included the introduction of eye-tracking technology. However, when new and additional kinds of data are processed, emerging risks for data protection might arise. This paper will, therefore, discuss the compatibility of eye-tracking devices for virtual and augmented reality environments with the European Union General Data Protection Regulation (GDPR). Being the GDPR considered a worldwide role model in terms of fundamental rights protection, the compatibility of such devices with one of the most severe data protection regimes will be put to the hardest test. The paper will do so by analyzing the state of the art of the technology, its use in headsets and glasses for virtual and augmented reality Metaverse environments, and the potential risks that such use might entail for data protection. After that, such risks will be confronted with the relevant applicable provisions of the GDPR. Finally, the paper will issue policy recommendations.

Transgender persons' view on previous fertility decision-making and current infertility: a qualitative study.

How do adult transgender and gender diverse (TGD) people, who are infertile due to prior gender-affirming treatment, view their current infertility and their reproductive decisions made in the past? In a time where sterilization was mandatory, transgender adolescents prioritized gender-affirming treatment over their future fertility and would make the same choice today despite emotional challenges related to infertility experienced by some. Under transgender law in the Netherlands, sterilization was required for legal gender recognition until 2014, resulting in permanent infertility. The long-term consequences of this iatrogenic infertility in transgender adolescents who have now reached adulthood remain underexplored. Qualitative study design based on 21 in-depth one-on-one semi-structured interviews. TGD people in a stage of life where family planning may be a current topic were eligible for participation. They all received gender-affirming treatment in adolescence prior to the legislation change in 2014. A purposeful sampling technique was used from participants of another ongoing study. Eleven people assigned female at birth and ten people assigned male at birth were included. Interview transcripts were thematically analysed using a modified version of Braun and Clarke's six steps theory. Six main themes were generated: (i) personal considerations regarding fertility and fertility preservation in the past; (ii) external considerations regarding fertility and fertility preservation in the past; (iii) current vision on past considerations and decisions; (iv) Current experiences and coping with infertility; (v) future family building; (vi) advice regarding fertility and fertility preservation decision-making. Selection, recall, and choice supportive bias may play a role in interpreting our results. This study highlights the importance of tailored counselling and comprehensive information on fertility preservation for transgender individuals, especially adolescents, undergoing gender-affirming treatment. N/A. N/A.

Wavelength‐Selective Photodetector and Neuromorphic Visual Sensor Utilizing Intrinsic Defect Semiconductor

AbstractWith the rapid developments of Artificial Intelligence (AI) and the Internet of Things (IoT), increasingly intricate and expanding application scenarios are placing higher demands on current machine vision capabilities. Therefore, there is a pressing need to simultaneously achieve diverse functionalities, simple designs, and efficient computing in vision devices. Here, the study develops a two‐terminal optoelectronic device utilizing a single 2D intrinsic defect semiconductor In2S3. The device demonstrates wavelength‐selective photodetection and neuromorphic visual capabilities, attributed to defect‐related charge‐trapping/de‐trapping processes. As a photodetector, the device exhibits a high photoresponsivity of 473.6 A W−1, a high external quantum efficiency of 1.6 × 105%, and a fast rise/fall time of 0.3/1.4 ms at the wavelength of 359 nm. As an all‐in‐one neuromorphic visual device, optoelectronic‐driven fundamental synaptic functions, including paired‐pulse facilitation (PPF), short‐term plasticity (STP), long‐term plasticity (LTP), and “learning‐experience”, are successfully mimicked at the wavelength of 671 nm. Moreover, one‐shot recognition of the 12‐letter image “SHAN XI NORMAL” is achieved through an artificial convolutional neural network. This study provides a new strategy for developing compact high‐level intelligence systems for complex application scenarios.

Standard models of spatial vision mispredict edge sensitivity at low spatial frequencies

One well-established characteristic of early visual processing is the contrast sensitivity function (CSF) which describes how sensitivity varies with the spatial frequency (SF) content of the visual input. The CSF prompted the development of a now standard model of spatial vision. It represents the visual input by activity in orientation- and SF selective channels which are nonlinearly recombined to predict a perceptual decision. The standard spatial vision model has been extensively tested with sinusoidal gratings at low contrast because their narrow SF spectra isolate the underlying SF selective mechanisms. It is less studied how well these mechanisms account for sensitivity to more behaviourally relevant stimuli such as sharp edges at high contrast (i.e. object boundaries) which abound in the natural environment and have broader SF spectra. Here, we probe sensitivity to edges (2-AFC, edge localization) in the presence of broadband and narrowband noises. We use Cornsweet luminance profiles with peak frequencies at 0.5, 3 and 9 cpd as edge stimuli. To test how well mechanisms underlying sinusoidal contrast sensitivity can account for edge sensitivity, we implement a single- and a multi-scale model building upon standard spatial vision model components. Both models account for most of the data but also systematically deviate in their predictions, particularly in the presence of pink noise and for the lowest SF edge. These deviations might indicate a transition from contrast- to luminance-based detection at low SFs. Alternatively, they might point to a missing component in current spatial vision models.

Advancing pediatric drug development in South Asia: Current landscape and vision for the future.

The manuscript summarizes the outcomes of a one-day conference by the South Asian College of American College of Clinical Pharmacology (SAC-ACCP) in July 2023, at Bhopal. The theme of the conference was "Advancing pediatric drug development in South Asia." SAC-ACCP organized this event in Bhopal to foster the discipline of clinical pharmacology and to motivate researchers and physicians in the in the central part of India. The conference featured presentations on regional approaches to pediatric drug development in Asia by pediatric scientific experts from the pharmaceutical industry, regulatory agencies, as well as independent consultancies. The speakers highlighted several important aspects of the evolving regulatory landscape in India and proposed numerous actionable steps in acceleration of pediatric drug development. This commentary provides insights from presentations and the panel discussion at this conference and also makes an attempt to connect to similar discussions that occurred at the SAC-ACCP drug development conference in 2017.

Exploratory Descriptive on the Self-Confidence of Prospective Accountants Toward Economic Digitalization

One of the key characteristic features of change in the modern socio-economic environment is information, which manifested in both the dynamic development of the information within the communication technology and in the transformation of the information itself into a strategic resource for the entities’ welfare, especially for an economic entity inside the turbulence of an ever-changing world. Accounting is considered one of the fragments that is significantly impacted by the speeding up of digital transformation. Academics and practitioners have noted several difficulties and issue that comes to the surface concerning the decline of accounting functionality and the reporting value of the information for stakeholders. The existence of new technological capabilities such as artificial intelligence does not eliminate the possibility of alteration on the role of an accountant, and this can create tension for students majoring in accounting. Whether it is a threat or an opportunity for accounting development for the 'generation Z’ facing the AI era. The existing volatility assessment of the future accounting profession has contributed to the decline in motivation of the current generation to see the prestige of the accounting profession, and negatively affected the demand for accounting education. This study examines how future accountants undergo formal education in the face of the digital accounting era, provide actionable recommendations for individuals and organizations to build and maintain self-confidence in the context of Industry 5.0. The analysis used in this study is qualitative methods with phenomenological approaches analyze with QSR NVivo12 which leads to the conclusion that the current vision and role of an accountant who was previously called a record holder must develop to a bigger role that possesses a certain influence within the present-day market and society. The function of an accountant cannot be fully automated, due to the wide variety of accounting functions that require professional judgment based on systems of expertise, experience, and intuition. By achieving a comprehensive vision and role, the acceleration of accounting information technology will require the role of an accountant and not vice versa.